Investigating the Relationship Between Spatial Skills and Computer Science

The relationship between spatial skills training and computer science learning is unclear. Reported experiments provide tantalising, though not convincing, evidence that training a programming student's spatial skills may accelerate the development of their programming skills. Given the well-documented challenge of learning to program, such acceleration would be welcomed. Despite the experimental results, no attempt has been made to develop a model of how a linkage between spatial skills and computer science ability might operate, hampering the development of a sound research programme to investigate the issue further. This paper surveys the literature on spatial skills and investigates the various underlying cognitive skills involved. It poses a theoretical model for the relationship between computer science ability and spatial skills, exploring ways in which the cognitive processes involved in each overlap, and hence may influence one another. An experiment shows that spatial skills typically increase as the level of academic achievement in computer science increases. Overall, this work provides a substantial foundation for, and encouragement to develop, a major research programme investigating precisely how spatial skills training influences computer science learning, and hence whether computer science education could be significantly improved

SciPy 1.0: fundamental algorithms for scientific computing in Python.

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments

Does computer confidence relate to levels of achievement in ICT-enriched learning models?

Employer expectations have changed: university students are expected to graduate with computer competencies appropriate for their field. Educators are also harnessing technology as a medium for learning in the belief that information and communication technologies (ICT’s) can enliven and motivate learning across a wide range of disciplines. Alongside developing students’ computer skills and introducing them to the use of professional software, educators are also harnessing professional and scientific packages for learning in some disciplines. As the educational use of information and communication technologies increases dramatically, questions arise about the effects on learners. While the use of computers for delivery, support, and communication, is generally easy and unthreatening, higher-level use may pose a barrier to learning for those who lack confidence or experience. Computer confidence may mediate in how well students perform in learning environments that require interaction with computers. This paper examines the role played by computer confidence (or computer self-efficacy) in a technology-enriched science and engineering mathematics course in an Australian university. Findings revealed that careful and appropriate use of professional software did indeed enliven learning for the majority of students. However, computer confidence occupied a very different dimension to mathematics confidence: and was not a predictor of achievement in the mathematics tasks, not even those requiring use of technology. Moreover, despite careful and nurturing support for use of the software, students with low computer confidence levels felt threatened and disadvantaged by computer laboratory tasks. The educational implications of these findings are discussed with regard to teaching and assessment, in particular. The TCAT scales used to measure technology attitudes, computer confidence/self-efficacy and mathematics confidence are included in an Appendix. Well-established, reliable, internally consistent, they may be useful to other researchers. The development of the computer confidence scale is outlined, and guidelines are offered for the design of other discipline-specific confidence/self-efficacy scales appropriate for use alongside the computer confidence scale

Exploring Spatial Skills and Computing in Primary and Secondary Education

This workshop aims to break down the connection between spatial skills and STEM - particularly computing - and highlight existing research of value, presenting an argument for spatial skills instruction in schools. We will discuss known challenges and obstacles to delivery, and aim to collect further challenges from participants. We will then consider effective means of developing spatial skills, and measuring potential outcomes (particularly in computing science), that could be generally applied across multiple schools concurrently with limited training and resource costs. The resulting pack should be a theoretical solution which could potentially be practically implemented across multiple schools